To aid the clinician in evaluating the physiological status of an individual, so called polygraphic monitoring is used to record a variety of measurable physiological variables which can be reviewed to determine the fluctuations of one or more physiological functions. One example of a physiological function receiving intensive study in a clinical setting is the state of sleep in individuals. For several decades, long term recordings on paper of electroencephalograms (EEG) alone and in combination with other physiological data such as obtained from electrooculorgrams (EOG), and electromyograms (EMG), heart rate monitoring, and respiration have been used to study and classify the process of sleep. Typically, to reveal the cyclic fluctuation of the depth of sleep, a description of various physiological phenomena, such as EEG, EOG, EMG, etc., is made by the clinician for each page of the EEG, etc., recording. A set of describing parameters is then used to classify the sleep into, for example, five classes or stages. The resulting graph, which indicates the stage of sleep for each consecutive recording page, is called a hypnogram. Normally, such a graph shows a damped oscillation with a cycle duration of about 90 minutes.
In 1968, Rechtschaffen and Kales established criteria for the classification of sleep which today are commonly used in sleep research. EEG, EOG, and EMG variables are considered in this classification scheme, and attention is paid as well to the ongoing EEG background activity (amplitude and time index of EEG rhythms) as well as to certain transient patterns (K complexes, sleepspindles, sharp Vertex waves, theta bursting, etc.). Attention is also paid to rapid eye movements (REM) and muscle tension (EMG) measured at the chin. The criteria of Rechtschaffen and Kales classify the stages of sleep--I through IV and REM sleep--based on how the monitored physiological variables meet prescribed rules, for example, the occurrence of sleepspindles for stage II, and whether the variables lay within (or exceed) certain values (e.g., for Stage IV the amplitude of delta waves must exceed 75 microvolts for more than 50% of the time). These rules for classifying sleep are well known and referenced in standard physiology handbooks.
Sleep problems may arise in individuals when the sleep is polyphasic, when there is too little sleep, and when the sleep is superficial or shows many shifts and awakenings, even if these last only a few seconds (micro-arousals). To determine possible causes of such sleep disturbances, a series of additional physiological variables must be recorded (polysomnography) and their relationship with disturbance of sleep must be studied. Right and left anterior tibialis EMG will reveal myoclonus "restless legs" syndrome. Electrocardiogram (EKG) signals can detect heart arrhythmia. Measurements of the movements of the rib cage and abdomen, the nostril and oral air flow, the intercostal EMG and the blood oxygen saturation can detect impaired breathing, apnea, and the type of apnea, and can trace the interference thereof with the process of sleep.
Complicating the characterization of sleep using the criteria of Rechtschaffen and Kales is the fact that EEG characteristics may differ considerably from individual to individual (e.g., the amplitude of delta waves typically changes with age, and may be affected by the thickness of the scalp, etc.) and physiological peculiarities may occur particularly when testing insomniacs and when encountering borderline abnormal and pathological EEG signals (e.g., absence of alpha rhythms, sleepspindles, rapid eye movements, presence of epileptic paroxysmal activity, high muscle tension during REM, etc.). In clinical practice, therefore, the Rechtschaffen and Kales criteria are often applied in a flexible way, taking into account the individual's, EEG, EOG and EMG characteristics and pecularities, thereby yielding a more realistic classification of the sleep of a particular subject. In effect, the experience and judgment of the reviewing clinician are used to select or adjust the classification rules on a case by case basis.
Conventional automated sleep analysis systems typically carry out the classification of sleep using fixed Rechtschaffen and Kales criteria, thereby often giving rise to inconsistent and unreliable results, even if applied to a homogeneous subject group, for the reasons noted above. The results are particularly vulnerable to bias and inconsistency if applied to a variety of subject groups using the same fixed criteria. Generally, conventional systems do not allow inspection of the results of the various steps of data reduction leading up to the classification of sleep stages, thereby making it impossible for the clinician to assess the quality and reliability of the final analysis and classification. The inability of such systems to allow the clinician to monitor and verify the accuracy of the data reduction steps reduces the confidence of the clinician in the end results and limits the acceptability of such systems in clinical settings.
Most conventional polygraphic physiological data analysis systems focus on a single physiological function (for example, sleep) and on one type of analysis (for example, calculation of the hypnogram). Such systems have only limited value in clinical diagnosis where assesment and exploration of time relationships between physiological functions is of primary importance. In the visual analysis of clinical long term recordings, phenomena are often considered that are not embodied in the definition of a "normal" physiological function (for example, alpha/delta sleep, increased beta activity as a consequence of medication). Some of these phenomena have a short time duration and require an analysis with higher time resolution than under normal physiological conditions (e.g., micro arousals, burst like delta waves indicating short periods of unstable deep sleep, and micro sleep during the day). Some are highly complex, such as those seen in the clinical long term study of epilepsy where combinations of polyspike and slow-wave patterns are seen in bursts of a few seconds with an irregualar repetition frequency during sleep, as opposed to the classical regular three per second spike and slow-wave pattern seen during the day. Conventional systems cannot trace the occurance of such a variety of clinically relevant signal patterns for which both high time resolution and sophisticated pattern detection are required to accommodate the short time duration and complexity of the signal, respectively.
In addition to the monitoring of physiological variables which are related to the sleep state, polygraphic recordings over long time periods are also of use in detecting and diagnosing other physiological conditions. For example, nocturnal penile tumescence (NPT) can be recorded during sleep to diagnose the causes of impotence. Polygraphic monitoring during the day is sometimes used to diagnose narcolepsy and to determine the severity of daytime sleepiness. Polygraphic monitoring during both night and daytime situations with at least eight channels of EEG can be used to detect and monitor the occurance of epileptic seizures. Using the recorded data, the type of epilepsy can be specified and the effects of treatment can be evaluated. The monitoring of traditional physiological functions in combination with the monitoring of the functioning of the brain is also becoming more commonly used in accute situations such as during surgery and in the monitoring of patients in the Intensive Care Unit.